Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Programming, Linear”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13Linked to original sources
PubMed2000

Partitioning of amino acids flowing to the abomasum into feed, bacterial, protozoal, and endogenous fractions.

We partitioned the flow of amino acids (AA) to the abomasum among rumen undegradable protein (RUP) and bacterial, protozoal, and endogenous fractions using four Holstein cows in midlactation that were equipped with ruminal and abomasal cannulas. A 2 x 2 factorial design with four diets, combinations of high or low ruminally degradable organic matter, and rumen degradable protein, was employed. Crude protein (CP) and AA contents of ruminal bacteria and protozoa and abomasal digesta were determined. Equations for the source compositions and in vivo flows of CP and 16 AA were then solved simultaneously with a linear program to estimate the contribution of RUP, bacterial, protozoal, and endogenous CP to AA flows. The flows of RUP and bacterial AA were not affected by diet. Low dietary RDP increased the flow of protozoal AA to the abomasum, but the ruminally degradable organic matter content of the diet did not affect protozoal AA flow. Across diets, RUP, bacterial, protozoal, and endogenous fractions provided 55, 33, 11, and <1% of the CP, and 62, 26, 12, and <1% of the AA that reached the abomasum. The linear program was a useful tool for partitioning AA that flows to the abomasum. The technique may also allow dietary effects on ruminal microbes and the AA profile of protein flowing to the duodenum to be better understood and perhaps manipulated.

Abomasum↗
PubMed2000

Special review: game theory to analyse management options in gastro-oesophageal reflux disease.

This study aims to demonstrate the applicability of linear programming to threshold analysis, using, as an example, patients with new onset of gastro-oesophageal reflux disease (GERD). The choice amongst competing management options is modelled as a decision tree, using threshold analysis, as well as an m x n matrix on an Excel spreadsheet. The different options of medical management correspond to the m rows, whilst the different disease states correspond to the n columns of the matrix. Each number at the intersection of a row and a column represents the outcome associated with that particular combination of management and disease state. The threshold values are calculated by the built-in functions for linear programming of Excel using its Solver tool. Varying the cost estimates in the sensitivity analysis translates into solving a set of different matrices. Threshold analysis provides a formalism to phrase problems of medical decision analysis in a concise fashion.

Cost-Benefit Analysis↗
PubMed2006

Analysis of optimal phenotypic space using elementary modes as applied to Corynebacterium glutamicum.

BACKGROUND: Quantification of the metabolic network of an organism offers insights into possible ways of developing mutant strain for better productivity of an extracellular metabolite. The first step in this quantification is the enumeration of stoichiometries of all reactions occurring in a metabolic network. The structural details of the network in combination with experimentally observed accumulation rates of external metabolites can yield flux distribution at steady state. One such methodology for quantification is the use of elementary modes, which are minimal set of enzymes connecting external metabolites. Here, we have used a linear objective function subject to elementary modes as constraint to determine the fluxes in the metabolic network of Corynebacterium glutamicum. The feasible phenotypic space was evaluated at various combinations of oxygen and ammonia uptake rates. RESULTS: Quantification of the fluxes of the elementary modes in the metabolism of C. glutamicum was formulated as linear programming. The analysis demonstrated that the solution was dependent on the criteria of objective function when less than four accumulation rates of the external metabolites were considered. The analysis yielded feasible ranges of fluxes of elementary modes that satisfy the experimental accumulation rates. In C. glutamicum, the elementary modes relating to biomass synthesis through glycolysis and TCA cycle were predominantly operational in the initial growth phase. At a later time, the elementary modes contributing to lysine synthesis became active. The oxygen and ammonia uptake rates were shown to be bounded in the phenotypic space due to the stoichiometric constraint of the elementary modes. CONCLUSION: We have demonstrated the use of elementary modes and the linear programming to quantify a metabolic network. We have used the methodology to quantify the network of C. glutamicum, which evaluates the set of operational elementary modes at different phases of fermentation. The methodology was also used to determine the feasible solution space for a given set of substrate uptake rates under specific optimization criteria. Such an approach can be used to determine the optimality of the accumulation rates of any metabolite in a given network.

Corynebacterium glutamicum↗
PubMed1999

Identification of optimal strategies for increasing whole arm strength using Karush-Kuhn-Tucker multipliers.

OBJECTIVE: The purpose of this study was to develop a computer model for identifying muscles critical to improving functional upper extremity strength. DESIGN: A three-dimensional biomechanical model of the upper extremity was developed, and the predictions were compared to maximal arm strength data collected from healthy volunteers. BACKGROUND: Although several optimization-based mathematical models of the shoulder have been developed, none have utilized the mathematical properties of the Karush-Kuhn-Tucker multipliers to efficiently estimate the effect of strengthening individual muscles on functional strength of the whole arm. METHODS: A static three-dimensional biomechanical model of the glenohumeral, radio-humeral, ulno-humeral and wrist joints was developed for predicting maximal hand exertion forces. The model was formulated as a linear program. Constraints consisted of moment equilibrium conditions and limits on maximum and minimum allowable muscle forces. Predicted arm strengths were compared to maximal pull strength measurements made on 10 subjects (5 male; 5 female). The task involved pulling toward the mid-sagittal plane of the body with the arm flexed 45 degrees. The Karush-Kuhn-Tucker variables associated with the maximal limits on muscle force were computed to estimate the effect of altering the strength of individual muscles on functional arm strength. RESULTS: Maximum pull strengths were predicted well by the model. Karush-Kuhn-Tucker values ranged from 0 (for muscles not at their upper force limits) to 0.11 for the flexor carpi radialis and pectoralis major muscles. Karush-Kuhn-Tucker multipliers were found to be insensitive to the assumed specific tension of muscle. CONCLUSIONS: Upper extremity strength can be predicted from musculoskeletal geometry and physiology using linear programming. RELEVANCE: Karush-Kuhn-Tucker multipliers associated with the muscle force upper limits give insight into the effect of strengthening individual muscles on whole arm exertion strength. Such an analysis may provide insight into the development of optimal rehabilitation protocols.

Adult↗
PubMed2002

Calculating a potential increase in hospital margin for elective surgery by changing operating room time allocations or increasing nursing staffing to permit completion of more cases: a case study.

UNLABELLED: Administrators routinely seek to increase contribution margin (revenue minus variable costs) to better cover fixed costs, provide indigent care, and meet other community service responsibilities. Hospitals with high operating room (OR) utilizations can allocate OR time for elective surgery to surgeons based partly on their contribution margins per hour of OR time. This applies particularly when OR caseload is limited by nursing recruitment. From a hospital's annual accounting data for elective cases, we calculated the following for each surgeon's patients: variable costs for the entire hospitalization or outpatient visit, revenues, hours of OR time, hours of regular ward time, and hours of intensive care unit (ICU) time. The contribution margin per hour of OR time varied more than 1000% among surgeons. Linear programming showed that reallocating OR time among surgeons could increase the overall hospital contribution margin for elective surgery by 7.1%. This was not achieved simply by taking OR time from surgeons with the smallest contribution margins per OR hour and giving it to the surgeons with the largest contribution margins per OR hour because different surgeons used differing amounts of hospital ward and ICU time. We conclude that to achieve substantive improvement in a hospital's perioperative financial performance despite restrictions on available OR, hospital ward, or ICU time, contribution margin per OR hour should be considered (perhaps along with OR utilization) when OR time is allocated. IMPLICATIONS: For hospitals where elective surgery caseload is limited by nursing recruitment, to increase one surgeon's operating room time either another surgeon's time must be decreased, nurses need to be paid a premium for working longer hours, or higher-priced "traveling" nurses can be contracted. Linear programming was performed using Microsoft Excel to estimate the effect of each of these interventions on hospital contribution margin.

Elective Surgical Procedures↗
PubMed1997

A linear goal programming model for human resource allocation in a health-care organization.

This paper presents the development of a goal programming (GP) model as an aid to strategic planning and allocation for limited human resources in a health-care organization. The purpose of this study is to assign the personnel to the proper shift hours that enable management to meet the objective of minimizing the total payroll costs while patients are satisfied. A GP model is illustrated using the data provided by a health-care organization in the midwest area. The goals are identified and prioritized. The model result is examined and a sensitivity analysis is performed to improve the model applicability. The GP model application adds insight to the planning functions of resource allocation in the health-care organizations. The proposed model is easily applicable to other human resource planning process.

Algorithms↗
PubMed1983

Enhanced polypeptide synthesis programmed by linear DNA fragments in cell-free extracts lacking exonuclease V.

Preparation of an in vitro coupled transcription-translation system from E. coli strains lacking exonuclease V has greatly improved the system for use with added linear DNA fragments. In fact, in extracts of these mutants linear fragments are stable for several hours. However the cell extracts show a high level of endogenous background. To avoid this complication extracts were prepared at 30 degrees C from a mutant carrying a temperature-sensitive exonuclease V. Polypeptides coded by a specific DNA region, e.g., delineated by restriction endonuclease sites, can now be easily identified.

DNA, Bacterial↗
PubMed1986

Non-linear fitting program for biological data.

A simple microcomputer program written in Microsoft Basic estimates pharmacokinetic parameters using the coordinate search technique to minimize the sum of squared errors. The program developed for portable computers combines a plot of data and curve fitting so as to find rapidly the initial parameters with the subsequent optimization of the parameter estimate.

Computers↗
PubMed2006

Modeling small-scale dairy farms in central Mexico using multi-criteria programming.

Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multi-criteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, ryegrass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.

Animal Feed↗
PubMed1988

A non-linear goal programming approach to modeling intraregional economic development.

"This paper provides a one-period normative model that may be used as a guide or benchmark by which the economic planner may develop policies and plans for regional economic development. The model can accomodate a region that could be as large as a small country or as small as a city, provided sufficient relevant data are available." The authors outline "a procedure for modeling and solving economic planning and analysis problems with 'intergoal trade-offs' while retaining the deviational variable as a measure of satisfaction....[They present] a generalized regional polynomial goal programming model with some suggested objectives and constraints [and illustrate] the approach with a hypothetical example."

Economics↗
PubMed2000

Least-cost ration formulations for Holstein dairy heifers by using linear and stochastic programming.

Four mathematical programming models were developed to formulate rations for large breed replacement dairy heifers in each of 11 different weight classes from 50 to 550 kg and daily growth rates of 600, 700, and 800 g, with the objective of achieving a final calving weight of 600 kg. First, a base linear programming model was developed; then, to account for variability in the crude protein content of ration ingredients three other methods were used: right-hand side adjustment, incorporation of a safety margin, and stochastic programming. The average daily cost to calving, given a daily gain of 600, 700, and 800 g, was $0.62, $0.64, and $0.68, respectively. The total feed cost to 600 kg was $89.87 more for a growth rate of 600 over 800 g/d. The stochastic programming model performed better, on the bases of cost and protein-feeding, than did the right-hand side adjustment or the safety margin methods. The stochastic programming model over-adjusted crude protein by 5% and cost an average of 3.5% more than the linear programming solution for a dairy heifer growing at 800 g/d with a desired probability of 80% of crude protein intake achieving the NRC minimum. The other two methods over-adjusted crude protein by 10 and 13% and cost an extra 5.5 and 7.6%, respectively, for the right-hand side adjustment and the safety margin methods.

Animal Feed↗
PubMed1989

[Maximization of economic yield, minimum cost optimal diets and cultivation diversification for small scale farmers of the highland region of Guatemala].

The present study was conducted as part of an evaluation of the economic and nutritional effects of a crop diversification program for small-scale farmers in the Western highlands of Guatemala. Linear programming models are employed in order to obtain optimal combinations of traditional and non-traditional food crops under different ecological conditions that: a) provide minimum cost diets for auto-consumption, and b) maximize net income and market availability of dietary energy. Data used were generated by means of an agroeconomic survey conducted in 1983 among 726 farming households. Food prices were obtained from the Institute of Agrarian Marketing; data on production costs, from the National Bank of Agricultural Development in Guatemala. The gestation periods for each crop were obtained from three different sources, and then averaged. The results indicated that the optimal cropping pattern for the minimum-cost diets for auto consumption include traditional foods (corn, beans, broad bean, wheat, potato), non-traditional foods (carrots, broccoli, beets) and foods of animal origin (milk, eggs). A significant number of farmers included in the sample did not have sufficient land availability to produce all foods included in the minimum-cost diet. Cropping patterns which maximize net incomes include only non-traditional foods: onions, carrots, broccoli and beets for farmers in the low highland areas, and raddish, broccoli, cauliflower and carrots for farmers in the higher parts. Optimal cropping patterns which maximize market availability of dietary energy include traditional and non-traditional foods; for farmers in the lower areas: wheat, corn, beets, carrots and onions; for farmers in the higher areas: potato, wheat, raddish, carrots and cabbage.

Agriculture↗
PubMed2006

IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty.

In this study, an interval-parameter fuzzy-robust programming (IFRP) model is developed and applied to the planning of solid waste management systems under uncertainty. As an extension of the existing fuzzy-robust programming and interval-parameter linear programming methods, the IFRP can explicitly address system uncertainties with complex presentations. Parameters in the IFRP model can be represented as interval numbers and/or fuzzy membership functions, such that the uncertainties can be directly communicated into the optimization process and resulting solution. Furthermore, highly uncertain information for the lower and upper bounds of interval parameters that exist due to the complexity of the real world can be effectively handled through introducing the concept of fuzzy boundary interval. Consequently, robustness of the optimization process and solution can be enhanced. Results of the case study indicate that useful solutions for planning municipal solid waste management practices can be generated. They reflect a compromise between optimality and stability of the study system. Willingness to pay higher costs will guarantee the system stability; however, a desire to reduce the costs will run the risk of potential instability of the system. The results also suggest that the proposed hybrid methodology is applicable to practical problems that are associated with highly complex and uncertain information.

Algorithms↗
PubMed2004

Active set support vector regression.

This paper presents active set support vector regression (ASVR), a new active set strategy to solve a straightforward reformulation of the standard support vector regression problem. This new algorithm is based on the successful ASVM algorithm for classification problems, and consists of solving a finite number of linear equations with a typically large dimensionality equal to the number of points to be approximated. However, by making use of the Sherman-Morrison-Woodbury formula, a much smaller matrix of the order of the original input space is inverted at each step. The algorithm requires no specialized quadratic or linear programming code, but merely a linear equation solver which is publicly available. ASVR is extremely fast, produces comparable generalization error to other popular algorithms, and is available on the web for download.

Algorithms↗
PubMed2000

Estimating unit costs of nutrients from market prices of feedstuffs.

The determinations of nutrient costs and breakeven prices of feedstuffs are important activities in the field of nutritional economics. Current methods are either extensions of the Petersen method, which dates back to 1932, or mathematical programming methods generally set as linear programming problems. Both sets of methods have severe limitations that make them unsuitable or biased for deriving unit costs of nutrients and aggregate breakeven costs of feedstuffs in a given market. We propose a least-squares method that, under verifiable conditions, yields maximum likelihood estimates of unit costs of nutrients and breakeven prices of feedstuffs. Assumptions to the maximum likelihood estimates are verified with studentized residuals, leverage values, and variance inflation factors. The method has been programmed into a Windows application and can be used by those with little formal training in statistics.

Animal Feed↗